• Avinash S
• Vikas Mendhe

Autoimmune diseases are the kind of diseases in which immune system mistakenly attacks human body instead of foreign agents and Diabetic retinopathy is one of them. Early detection of these diseases is difficult because they can be easily misdiagnosed as other common ailments. Due to this, they are diagnosed at critical stage where most often treatment does not work. The solution is to come up with techniques for early detection so that proper treatment can avoid manifestation of mild symptoms into chronic disease. This paper focuses on Diabetic Retinopathy and proposes few techniques to automate its detection with highest accuracy. Objective is to detect the presence, type and level of severity using Convolutional Neural Network. Retinal Fundus image dataset available on Kaggle which is authentic and universal is used.

Machine learning, Diabetic Retinopathy, Convolutional Neural Network

"Detection of Diabetic Retinopathy using Convolutional Neural Network ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.d61-d67, April-2024, Available :http://www.jetir.org/papers/JETIR2404310.pdf

"Detection of Diabetic Retinopathy using Convolutional Neural Network ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppd61-d67, April-2024, Available at : http://www.jetir.org/papers/JETIR2404310.pdf